AI correctly predicted the Hangzhou Greentown win.
The match finished 3–2, validating the model's directional assessment.
Tracked markets vs full-time result
Each row compares the pre-match model lean to the full-time result.
- Market Prediction Result Outcome
- Over / Under 2.5 Over 2.5 Over 2.5 (5 goals) ✔ Correct
- Both Teams To Score BTTS Yes Yes ✔ Correct
- 1X2 Hangzhou Greentown Hangzhou Greentown ✔ Correct
- Correct Score Insights 2-1, 3-1, 2-0, 1-1, 3-0 3-2 ✖ Incorrect
Model vs Closing Market
| Outcome | Model | Closing Market | Difference | Signal |
|---|---|---|---|---|
| Hangzhou Greentown | 67.4% | 47.1% | +20.2 pp | Model Edge |
| Draw | 18.3% | 24.3% | -6.0 pp | Market Higher |
| Dalian Zhixing | 14.3% | 28.5% | -14.2 pp | Market Higher |
The statistical model estimates Hangzhou Greentown's win probability at 67.4%, compared with the closing market's implied probability of 47.1%, a difference of 20.2 percentage points. This highlights a substantial disagreement between the model's assessment and the market consensus, rather than indicating which view is ultimately correct.
Model probabilities are generated from the statistical xG model using a Poisson distribution. Closing market probabilities are derived from consensus closing 1X2 odds after margin removal. Values represent implied probabilities rather than betting recommendations. Closing snapshot: PRE1.
After full time, the model's directional lean matched the result (Hangzhou Greentown win 3–2).
Post Match Insights
What worked
- Expected goals projected a high-scoring match (ΣxG 3.87) — 5 goals materialised
- Hangzhou Greentown attacking xG significantly stronger (2.66 vs 1.21)
- Both Teams To Score (Yes) matched the full-time result
What failed
- Exact score: outside the model's top score bins
Market lesson
Large model–market gaps do not automatically mean the market is right. Here the closing market priced Hangzhou Greentown more conservatively (47.2% vs model 67.4%, 20.2 pp), but the model's lean was validated (Hangzhou Greentown win 3–2).
Prediction Timeline
How this prediction moved from forecast to full-time review.
-
Jul 26, 2026 · 14:34 UTC Forecast generated
- Model 1X2 · Hangzhou Greentown 67.4% · Draw 18.3% · Dalian Zhixing 14.3%
- xG · Hangzhou Greentown 2.66 — Dalian Zhixing 1.21
-
Jul 26, 2026 · 11:30 UTC Opening odds snapshot PRE30
- 1X2 odds · Hangzhou Greentown 2.04 · Draw 3.95 · Dalian Zhixing 3.37
- Implied 1X2 · Hangzhou Greentown 47.1% · Draw 24.3% · Dalian Zhixing 28.5%
- Bookmaker · Pinnacle
-
Jul 26, 2026 · 11:59 UTC Closing snapshot recorded PRE1
- 1X2 odds · Hangzhou Greentown 2.04 · Draw 3.95 · Dalian Zhixing 3.37
- Implied 1X2 · Hangzhou Greentown 47.1% · Draw 24.3% · Dalian Zhixing 28.5%
- Bookmaker · Pinnacle
-
Jul 26, 2026 · 12:00 UTC Kickoff
-
FT Full-time result Hangzhou Greentown win · 3–2
-
FT Prediction validated Directional lean matched full-time result
-
Archived Prediction review
Historical Snapshot
Frozen at kickoff — the model output as it stood before the match started.
Historical label: Originally displayed as "Wait for validation".
Pre-match metrics (historical context)
- Validation: Warning
- Large market gap (20 pp)
- High xG deviation from league baseline (97%+)
- Strong model lean
- Pricing remains divergent
- Validation warning
Validation Report
Immutable SnapshotProbability Calibration
- Expected: 67.4%
- Historical Bucket: 65–70% — Building sample
Model Performance
This prediction contributes to:
- Primary Bets ROI (180d): -100.0%
Review FAQ
- How accurate was the prediction?
- This page grades directional markets (1X2, Over/Under 2.5, BTTS) against the full-time result. The prediction grade reflects how many of those tracked markets matched reality.
- What does xG Accuracy measure?
- xG Accuracy compares the model's pre-match expected-goals profile to the actual scoreline — not whether every market hit. A strong directional review can coexist with a moderate xG accuracy score.
- Why wasn't the exact score predicted?
- Correct-score outcomes are low-probability tails even when the model reads the match profile well. We highlight top score bins for context; missing the exact line does not invalidate a directional review.
- Does this improve the AI record?
- Each finished match is logged in our validation pipeline. Aggregated hit rates and CLV studies are published separately — this page is the per-match audit trail.
Predictions are for informational purposes only. Always gamble responsibly and within your limits. Past performance does not guarantee future results.
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Super League — Standings
| # | TEAM | MP | W | D | L | PTS |
|---|---|---|---|---|---|---|
| 1 | Chengdu Better City | 26 | 15 | 7 | 4 | 52 |
| 2 | Dalian Zhixing | 26 | 12 | 4 | 10 | 40 |
| 3 | Beijing Guoan | 26 | 11 | 10 | 5 | 38 |
| 4 | Yunnan Yukun | 26 | 11 | 5 | 10 | 38 |
| 5 | Qingdao Youth Island | 26 | 8 | 14 | 4 | 38 |
| 6 | Shandong Luneng | 26 | 13 | 4 | 9 | 37 |
| 7 | SHANGHAI SIPG | 26 | 10 | 8 | 8 | 33 |
| 8 | Shanghai Shenhua | 26 | 12 | 5 | 9 | 31 |
| 9 | Chongqing Tongliang Long | 26 | 7 | 10 | 9 | 31 |
| 10 | Hangzhou Greentown | 26 | 10 | 6 | 10 | 31 |
| 11 | Sichuan Jiuniu | 26 | 8 | 4 | 14 | 28 |
| 12 | Henan Jianye | 26 | 8 | 9 | 9 | 27 |
| 13 | Shenyang Urban | 26 | 7 | 4 | 15 | 25 |
| 14 | Tianjin Teda | 26 | 9 | 8 | 9 | 25 |
| 15 | Wuhan Three Towns | 26 | 5 | 11 | 10 | 21 |
| 16 | Qingdao Jonoon | 26 | 6 | 3 | 17 | 14 |
| # | TEAM | MP | GS | GC | +/- | PTS |
|---|---|---|---|---|---|---|
| 1 | Yunnan Yukun | 26 | 54 | 51 | +3 | 38 |
| 2 | Shanghai Shenhua | 26 | 52 | 46 | +6 | 31 |
| 3 | Chengdu Better City | 26 | 51 | 30 | +21 | 52 |
| 4 | Beijing Guoan | 26 | 49 | 33 | +16 | 38 |
| 5 | Shandong Luneng | 26 | 46 | 43 | +3 | 37 |
| 6 | Hangzhou Greentown | 26 | 45 | 43 | +2 | 31 |
| 7 | SHANGHAI SIPG | 26 | 40 | 33 | +7 | 33 |
| 8 | Wuhan Three Towns | 26 | 39 | 46 | -7 | 21 |
| 9 | Dalian Zhixing | 26 | 38 | 42 | -4 | 40 |
| 10 | Tianjin Teda | 26 | 36 | 32 | +4 | 25 |
| 11 | Sichuan Jiuniu | 26 | 34 | 45 | -11 | 28 |
| 12 | Shenyang Urban | 26 | 34 | 47 | -13 | 25 |
| 13 | Qingdao Jonoon | 26 | 34 | 53 | -19 | 14 |
| 14 | Henan Jianye | 26 | 33 | 35 | -2 | 27 |
| 15 | Qingdao Youth Island | 26 | 31 | 32 | -1 | 38 |
| 16 | Chongqing Tongliang Long | 26 | 27 | 32 | -5 | 31 |
| # | TEAM | MP | xG | xGC | +/- | PTS |
|---|---|---|---|---|---|---|
| 1 | Beijing Guoan | 26 | 4.4 | 0.1 | +4.3 | 38 |
| 2 | Shenyang Urban | 26 | 2.8 | 0.8 | +2.0 | 25 |
| 3 | Tianjin Teda | 26 | 1.5 | 0.6 | +0.9 | 25 |
| 4 | Chengdu Better City | 26 | 2.1 | 1.5 | +0.6 | 52 |
| 5 | Qingdao Youth Island | 26 | 1.8 | 1.2 | +0.6 | 38 |
| 6 | Yunnan Yukun | 26 | 2.6 | 2.3 | +0.3 | 38 |
| 7 | Dalian Zhixing | 26 | 2.3 | 2.0 | +0.3 | 40 |
| 8 | Hangzhou Greentown | 26 | 1.7 | 1.5 | +0.2 | 31 |
| 9 | Shanghai Shenhua | 26 | 1.5 | 1.7 | -0.2 | 31 |
| 10 | Wuhan Three Towns | 26 | 2.0 | 2.3 | -0.3 | 21 |
| 11 | Qingdao Jonoon | 26 | 1.5 | 2.1 | -0.6 | 14 |
| 12 | SHANGHAI SIPG | 26 | 1.2 | 1.8 | -0.6 | 33 |
| 13 | Sichuan Jiuniu | 26 | 0.6 | 1.5 | -0.9 | 28 |
| 14 | Chongqing Tongliang Long | 26 | 0.8 | 2.8 | -2.0 | 31 |
| 15 | Shandong Luneng | 26 | 2.4 | 7.0 | -4.6 | 37 |
| 16 | Henan Jianye | 26 | — | — | — | 27 |